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Shape And Layout Optimization Of Structural Sys...

Topology/shape optimization is an important problem in most engineering systems for lightweight, performance enhancement, and cost reduction. EDLab is conducting researches on topology/shape optimization on structural system (e.g. civil structures, aircraft), multiphysical system (e.g. energy harvesting devices).

Shape and Layout Optimization of Structural Sys...

Aircraft wing system design: This research aims at founding a design framework for aircraft subsystem layout using design optimization methodologies. An aircraft system is very complex with its various subsystems: control system (flight control, engine control), fuel system, hydraulic system, and structural system. An advanced systematic design approach is needed for effective packaging of multiple subsystems while satisfying load-carrying performance and minimizing weight for energy efficiency. The proposed design framework provides multiple Pareto solutions by performing the consecutive two design steps: (i) subsystem allocation, and (ii) structural topology optimization

Compliance = 1.238 without subsystem relocation (left) and 1.000 with relocation (right)Load Path Design: Many failures in load-carrying structures occur due to error in calculating load path. For example, the certification failure in Boeing 787 assembly was caused by error in estimating load distribution between upper and lower fasteners of the center wingbox. It was also reported that two thirds of missed steady state and dynamic loads cases in Boeing for last 30 years were caused by inadequate load analysis. Even if the external limit loads and design loads are well defined, it is difficult to analyze/evaluate accurate internal loads that are applied various joints of complex systems, which can cause overload and early joint failure. Instead of trying to analyze internal load for a given joint configuration, the main objective of this paper is to design/control internal load path of load-carrying structures using a new topology optimization strategy. A new topology optimization formulation with a local control of interface load is formulated, to minimize the structural volume subject to constraints on the ratio of multiple internal interface loads (or joint loads).

Topology optimization (TO) is a mathematical method that optimizes material layout within a given design space, for a given set of loads, boundary conditions and constraints with the goal of maximizing the performance of the system. Topology optimization is different from shape optimization and sizing optimization in the sense that the design can attain any shape within the design space, instead of dealing with predefined configurations.

The current proliferation of 3D printer technology has allowed designers and engineers to use topology optimization techniques when designing new products. Topology optimization combined with 3D printing can result in less weight, improved structural performance and shortened design-to-manufacturing cycle. As the designs, while efficient, might not be realisable with more traditional manufacturing techniques.[citation needed]

Layout or topology optimization deals with the selection of the best configuration for structural systems and constitutes one of the newest and most rapidly expanding fields of structural design, although some of its basic concepts were established almost a century ago. While mathematically and computationally perhaps the most challenging, it is also economically the most rewarding design task. This review article is based on a unified formulation and covers in detail both exact, analytical methods and approximate, discretized methods of layout optimization. Although discretized solutions are unavoidable for most practical, real-world problems, only explicit analytical solutions provide (i) a reliable means for checking the validity and convergence of numerical methods and (ii) a basis for assessing the relative economy of other designs. Moreover, some of the most efficient new numerical methods of layout optimization are iterative versions of analytical methods. Particularly promising are recent extensions of the exact layout theory to multiload, multipurpose elastic systems.

However, the best way to perfect your shipping area and shipping process is through proper warehouse storage optimization. Make sure to identify your most popular products and keep them near the shipping area, with the second most popular behind those, and so on. This is easier to do with a U-shaped and L-shaped layout.

The process of optimizing building designs requires developing several architectural and structural layout alternatives. Traditionally, limited number of design iterations can be conducted manually, which is time consuming and results in non-optimum designs in terms of limited functionality or high costs. The goal of this research is to develop an advanced Building Information Modeling (BIM) model for automating and optimizing design of building layouts and structural elements to reach minimum construction cost while abiding by the functionality constraints of the architectural design. The developed model integrates concepts from structural design, BIM modeling, and computer programming into one advanced optimization framework. The model was tested and validated in 11 case studies and is found to reduce the structural materials cost by up to 15% per floor without compromising the defined space requirements.

While a BIM-based workflow should enable overall information management throughout the lifecycle of a building, it is still significantly reliant on manual intervention7. As a result, there has been a growth in interest in automated workflows based on BIM to promote its usage and improve its potential efficiency8. For example9, developed a data model for integrating risk assessment of building conditions into BIM; where they automated the data transfer process and improve consistency and dependability for better visualization of conditions and causality analysis. El Mourabit10 developed a software for automating and optimizing concrete beam bridges. In another attempt11, investigated the automation trends of bridge design and highlighted the importance of automation in structural design in general as an important area to tackle. Earlier12, presented an optimization model for optimizing the design of prestressed concrete bridges. Other optimization models for design of bridges include those of13,14,15,16.

When it comes to buildings, design optimization models are not abundant and there is a need for further research in this area. For example17, developed a model for optimizing the cost of precast concrete slabs using evolutionary algorithms. Their model uses inputs such as the floor dimensions and live load to eventually provide structural design alternatives and arrange them. This model is able to design parameters such as the layout, dimensions, and reinforcement of the precast slabs. In another research18, developed a model for automating the design of flat slabs in concrete buildings using a hybrid optimization method. Other similar models are those of19,20,21,22.

There is a gap when it comes to BIM optimization models for traditional concrete systems such as solid slabs and flat slabs, which can be attributed to the complexities involved with their designs when compared to linear and straight-forward elements such as bridge beams. In addition, all of the discussed previous research concerning building design assumes fixed dimensions or fixed layouts of the floor slabs. In reality, structural engineers should have some flexibility to discuss the building layouts and may propose changes to the architects in order to optimize the structural design. In other words, there is some flexibility in the architectural design to shift some walls and columns within boundaries specified by the architect to fulfill certain functionality constraints to achieve optimum design. As such, optimization models should not assume fixed room dimensions. This research attempts to cover the above-mentioned gaps.

The goal of this research is to develop a model for automating and optimizing design of building layouts and structural elements for reaching minimum construction cost while abiding by the functionality constraints of the architectural design. The outputs from this model can have multiple uses, including developing an automated optimization framework for integrating the architectural and structural design of buildings, reaching optimum utilization of the functionality of the architectural design, and interpreting the optimum cost savings of the structural elements during the conceptual design phase of the construction projects. This framework can support the decision-making process between the architectural and structural design aspects in determining the best design alternative that is safe, satisfies architectural design and minimize cost. The framework maps the design principles and procedures from the international standard building codes into a developed mathematical model that can design different structural elements, including indeterminate structural elements. It also can act as a preliminary cost estimating tool that can evaluate the various design alternatives compared to a set budget.

The research utilizes and integrates concepts from structural design, BIM modeling, and computer programming into one advanced optimization framework. The research methodology is demonstrated in Fig. 1. First, a Cartesian coordinate system workflow is developed. In this workflow, algorithms are developed and used to convert the BIM architectural design into a more advanced state which model automated structural design. The inputs to this module are the architectural design, the architectural space limits such as different rooms boundaries and boundaries limits in both 2D directions, and the structural design inputs, which are mainly the required loads Material properties. The developed algorithms in this module are: grid and structural columns detection, Cartesian point arrangement, determination of geometric levels, and division of structural slabs. Details of these steps are described later in the manuscript. Second, a module for automating design of concrete it developed. In such module, automated design of slabs (solid and flat slabs) and beams is performed according to codes of practice. Third, an optimization module is developed where the user can choose their required design objective function such as optimizing the concrete quantities, steel quantities, or both. The model chooses a random initial population, then genetic generation and sorting loops to reach the required optimization results. The main idea is to allow the software to examine the proposed system and layout and perform optimization that includes repeated structure design. Each time a structural design is reached, a new model cost is computed then iterations take place to reach the final optimum design that is safe, applicable, and cost-efficient. After that, the developed framework is tested on different case studies to validate its effectiveness in reflecting the desired results. Detailed description is provided later in the manuscript. 041b061a72


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